package jalview.math;
import static org.testng.Assert.assertEquals;
+import static org.testng.Assert.assertFalse;
+import static org.testng.Assert.assertNotSame;
+import static org.testng.Assert.assertNull;
+import static org.testng.Assert.assertTrue;
import static org.testng.Assert.fail;
import java.util.Arrays;
+import java.util.Random;
import org.testng.annotations.Test;
+import org.testng.internal.junit.ArrayAsserts;
public class MatrixTest
{
+ final static double DELTA = 0.000001d;
+
@Test(groups = "Timing")
public void testPreMultiply_timing()
{
- int rows = 500;
- int cols = 1000;
+ int rows = 50; // increase to stress test timing
+ int cols = 100;
double[][] d1 = new double[rows][cols];
double[][] d2 = new double[cols][rows];
Matrix m1 = new Matrix(d1);
@Test(groups = "Functional")
public void testPreMultiply()
{
- MatrixI m1 = new Matrix(new double[][] { { 2, 3, 4 } }); // 1x3
- MatrixI m2 = new Matrix(new double[][] { { 5 }, { 6 }, { 7 } }); // 3x1
+ Matrix m1 = new Matrix(new double[][] { { 2, 3, 4 } }); // 1x3
+ Matrix m2 = new Matrix(new double[][] { { 5 }, { 6 }, { 7 } }); // 3x1
/*
* 1x3 times 3x1 is 1x1
assertEquals(m3.getRow(0)[1], 25d);
}
+ @Test(groups = "Functional")
+ public void testCopy()
+ {
+ Random r = new Random();
+ int rows = 5;
+ int cols = 11;
+ double[][] in = new double[rows][cols];
+
+ for (int i = 0; i < rows; i++)
+ {
+ for (int j = 0; j < cols; j++)
+ {
+ in[i][j] = r.nextDouble();
+ }
+ }
+ Matrix m1 = new Matrix(in);
+
+ Matrix m2 = (Matrix) m1.copy();
+ assertNotSame(m1, m2);
+ assertTrue(matrixEquals(m1, m2));
+ assertNull(m2.d);
+ assertNull(m2.e);
+
+ /*
+ * now add d and e vectors and recopy
+ */
+ m1.d = Arrays.copyOf(in[2], in[2].length);
+ m1.e = Arrays.copyOf(in[4], in[4].length);
+ m2 = (Matrix) m1.copy();
+ assertNotSame(m2.d, m1.d);
+ assertNotSame(m2.e, m1.e);
+ assertEquals(m2.d, m1.d);
+ assertEquals(m2.e, m1.e);
+ }
+
/**
* main method extracted from Matrix
*
assertEquals(Matrix.sign(1, 2), 1d);
assertEquals(Matrix.sign(1, 0), 1d);
}
+
+ /**
+ * Helper method to make values for a sparse, pseudo-random symmetric matrix
+ *
+ * @param rows
+ * @param cols
+ * @param occupancy
+ * one in 'occupancy' entries will be non-zero
+ * @return
+ */
+ public double[][] getSparseValues(int rows, int cols, int occupancy)
+ {
+ Random r = new Random(1729);
+
+ /*
+ * generate whole number values between -12 and +12
+ * (to mimic score matrices used in Jalview)
+ */
+ double[][] d = new double[rows][cols];
+ int m = 0;
+ for (int i = 0; i < rows; i++)
+ {
+ if (++m % occupancy == 0)
+ {
+ d[i][i] = r.nextInt() % 13; // diagonal
+ }
+ for (int j = 0; j < i; j++)
+ {
+ if (++m % occupancy == 0)
+ {
+ d[i][j] = r.nextInt() % 13;
+ d[j][i] = d[i][j];
+ }
+ }
+ }
+ return d;
+
+ }
+
+ /**
+ * Verify that the results of method tred() are the same if the calculation is
+ * redone
+ */
+ @Test(groups = "Functional")
+ public void testTred_reproducible()
+ {
+ /*
+ * make a pseudo-random symmetric matrix as required for tred/tqli
+ */
+ int rows = 10;
+ int cols = rows;
+ double[][] d = getSparseValues(rows, cols, 3);
+
+ /*
+ * make a copy of the values so m1, m2 are not
+ * sharing arrays!
+ */
+ double[][] d1 = new double[rows][cols];
+ for (int row = 0; row < rows; row++)
+ {
+ for (int col = 0; col < cols; col++)
+ {
+ d1[row][col] = d[row][col];
+ }
+ }
+ Matrix m1 = new Matrix(d);
+ Matrix m2 = new Matrix(d1);
+ assertMatricesMatch(m1, m2); // sanity check
+ m1.tred();
+ m2.tred();
+ assertMatricesMatch(m1, m2);
+ }
+
+ public static void assertMatricesMatch(MatrixI m1, MatrixI m2)
+ {
+ if (m1.height() != m2.height())
+ {
+ fail("height mismatch");
+ }
+ if (m1.width() != m2.width())
+ {
+ fail("width mismatch");
+ }
+ for (int row = 0; row < m1.height(); row++)
+ {
+ for (int col = 0; col < m1.width(); col++)
+ {
+ double v2 = m2.getValue(row, col);
+ double v1 = m1.getValue(row, col);
+ if (Math.abs(v1 - v2) > DELTA)
+ {
+ fail(String.format("At [%d, %d] %f != %f", row, col, v1, v2));
+ }
+ }
+ }
+ ArrayAsserts.assertArrayEquals("D vector", m1.getD(), m2.getD(),
+ 0.00001d);
+ ArrayAsserts.assertArrayEquals("E vector", m1.getE(), m2.getE(),
+ 0.00001d);
+ }
+
+ @Test(groups = "Functional")
+ public void testFindMinMax()
+ {
+ /*
+ * empty matrix case
+ */
+ Matrix m = new Matrix(new double[][] { {} });
+ assertNull(m.findMinMax());
+
+ /*
+ * normal case
+ */
+ double[][] vals = new double[2][];
+ vals[0] = new double[] {7d, 1d, -2.3d};
+ vals[1] = new double[] {-12d, 94.3d, -102.34d};
+ m = new Matrix(vals);
+ double[] minMax = m.findMinMax();
+ assertEquals(minMax[0], -102.34d);
+ assertEquals(minMax[1], 94.3d);
+ }
+
+ @Test(groups = { "Functional", "Timing" })
+ public void testFindMinMax_timing()
+ {
+ Random r = new Random();
+ int size = 1000; // increase to stress test timing
+ double[][] vals = new double[size][size];
+ double max = -Double.MAX_VALUE;
+ double min = Double.MAX_VALUE;
+ for (int i = 0; i < size; i++)
+ {
+ vals[i] = new double[size];
+ for (int j = 0; j < size; j++)
+ {
+ // use nextLong rather than nextDouble to include negative values
+ double d = r.nextLong();
+ if (d > max)
+ {
+ max = d;
+ }
+ if (d < min)
+ {
+ min = d;
+ }
+ vals[i][j] = d;
+ }
+ }
+ Matrix m = new Matrix(vals);
+ long now = System.currentTimeMillis();
+ double[] minMax = m.findMinMax();
+ System.out.println(String.format("findMinMax for %d x %d took %dms",
+ size, size, (System.currentTimeMillis() - now)));
+ assertEquals(minMax[0], min);
+ assertEquals(minMax[1], max);
+ }
+
+ /**
+ * Test range reversal with maximum value becoming zero
+ */
+ @Test(groups = "Functional")
+ public void testReverseRange_maxToZero()
+ {
+ Matrix m1 = new Matrix(
+ new double[][] { { 2, 3.5, 4 }, { -3.4, 4, 15 } });
+
+ /*
+ * subtract all from max: range -3.4 to 15 becomes 18.4 to 0
+ */
+ m1.reverseRange(true);
+ assertEquals(m1.getValue(0, 0), 13d, DELTA);
+ assertEquals(m1.getValue(0, 1), 11.5d, DELTA);
+ assertEquals(m1.getValue(0, 2), 11d, DELTA);
+ assertEquals(m1.getValue(1, 0), 18.4d, DELTA);
+ assertEquals(m1.getValue(1, 1), 11d, DELTA);
+ assertEquals(m1.getValue(1, 2), 0d, DELTA);
+
+ /*
+ * repeat operation - range is now 0 to 18.4
+ */
+ m1.reverseRange(true);
+ assertEquals(m1.getValue(0, 0), 5.4d, DELTA);
+ assertEquals(m1.getValue(0, 1), 6.9d, DELTA);
+ assertEquals(m1.getValue(0, 2), 7.4d, DELTA);
+ assertEquals(m1.getValue(1, 0), 0d, DELTA);
+ assertEquals(m1.getValue(1, 1), 7.4d, DELTA);
+ assertEquals(m1.getValue(1, 2), 18.4d, DELTA);
+ }
+
+ /**
+ * Test range reversal with minimum and maximum values swapped
+ */
+ @Test(groups = "Functional")
+ public void testReverseRange_swapMinMax()
+ {
+ Matrix m1 = new Matrix(
+ new double[][] { { 2, 3.5, 4 }, { -3.4, 4, 15 } });
+
+ /*
+ * swap all values in min-max range
+ * = subtract from (min + max = 11.6)
+ * range -3.4 to 15 becomes 18.4 to -3.4
+ */
+ m1.reverseRange(false);
+ assertEquals(m1.getValue(0, 0), 9.6d, DELTA);
+ assertEquals(m1.getValue(0, 1), 8.1d, DELTA);
+ assertEquals(m1.getValue(0, 2), 7.6d, DELTA);
+ assertEquals(m1.getValue(1, 0), 15d, DELTA);
+ assertEquals(m1.getValue(1, 1), 7.6d, DELTA);
+ assertEquals(m1.getValue(1, 2), -3.4d, DELTA);
+
+ /*
+ * repeat operation - original values restored
+ */
+ m1.reverseRange(false);
+ assertEquals(m1.getValue(0, 0), 2d, DELTA);
+ assertEquals(m1.getValue(0, 1), 3.5d, DELTA);
+ assertEquals(m1.getValue(0, 2), 4d, DELTA);
+ assertEquals(m1.getValue(1, 0), -3.4d, DELTA);
+ assertEquals(m1.getValue(1, 1), 4d, DELTA);
+ assertEquals(m1.getValue(1, 2), 15d, DELTA);
+ }
+
+ @Test(groups = "Functional")
+ public void testMultiply()
+ {
+ Matrix m = new Matrix(new double[][] { { 2, 3.5, 4 }, { -3.4, 4, 15 } });
+ m.multiply(2d);
+ assertEquals(m.getValue(0, 0), 4d, DELTA);
+ assertEquals(m.getValue(0, 1), 7d, DELTA);
+ assertEquals(m.getValue(0, 2), 8d, DELTA);
+ assertEquals(m.getValue(1, 0), -6.8d, DELTA);
+ assertEquals(m.getValue(1, 1), 8d, DELTA);
+ assertEquals(m.getValue(1, 2), 30d, DELTA);
+ }
+
+ @Test(groups = "Functional")
+ public void testConstructor()
+ {
+ double[][] values = new double[][] { { 1, 2, 3 }, { 4, 5, 6 } };
+ Matrix m = new Matrix(values);
+ assertEquals(m.getValue(0, 0), 1d, DELTA);
+
+ /*
+ * verify the matrix has a copy of the original array
+ */
+ assertNotSame(values[0], m.getRow(0));
+ values[0][0] = -1d;
+ assertEquals(m.getValue(0, 0), 1d, DELTA); // unchanged
+ }
+
+ @Test(groups = "Functional")
+ public void testEquals()
+ {
+ double[][] values = new double[][] { { 1, 2, 3 }, { 4, 5, 6 } };
+ Matrix m1 = new Matrix(values);
+ double[][] values2 = new double[][] { { 1, 2, 3 }, { 4, 5, 6 } };
+ Matrix m2 = new Matrix(values2);
+
+ double delta = 0.0001d;
+ assertTrue(m1.equals(m1, delta));
+ assertTrue(m1.equals(m2, delta));
+ assertTrue(m2.equals(m1, delta));
+
+ double[][] values3 = new double[][] { { 1, 2, 3 }, { 4, 5, 7 } };
+ m2 = new Matrix(values3);
+ assertFalse(m1.equals(m2, delta));
+ assertFalse(m2.equals(m1, delta));
+
+ // must be same shape
+ values2 = new double[][] { { 1, 2, 3 } };
+ m2 = new Matrix(values2);
+ assertFalse(m2.equals(m1, delta));
+
+ assertFalse(m1.equals(null, delta));
+ }
}
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